Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability. Trend test was performed to ensure that the developed model would follow the physical laws. Results show that the developed model outperforms the published correlations in term of absolute average percent relative error of 6.5%, and correlation coefficient of 96%.
The study aims to find out the extent to which several Iraqi institutional accreditation standards (governance and administration, scientific research, curricula) are applied in two public universities (Baghdad and Middle Technical University) and two private universities (Uruk and Al-Mansour College) by diagnosing strengths and weaknesses and proposing a mechanism and procedures to help educational institution aims to reduce or eliminate the gap. The study stems from the extent of application of several Iraqi institutional accreditation standards represented as it was worked on through observation and field coexistence to reach scientific and practical facts. The method of case study and comparison betwe
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Abstract
The traffic jams taking place in the cities of the Republic of Iraq in general and the province of Diwaniyah especially, causes return to the large numbers of the modern vehicles that have been imported in the last ten years and the lack of omission for old vehicles in the province, resulting in the accumulation of a large number of vehicles that exceed the capacity of the city's streets, all these reasons combined led to traffic congestion clear at the time of the beginning of work in the morning, So researchers chose local area network of the main roads of the province of Diwaniyah, which is considered the most important in terms of traffic congestion, it was identified fuzzy numbers for
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Abstract
The study was conducted in Baghdad and aimed to:
The impact of moving the educational activities in the conservation of literary
texts and the development of literary taste in the fifth grade students moral "by
verifying the validity of hypotheses Elsafreeten following forms:
The first hypothesis:
- There are no differences in women with statistical significance between means
of scores of students three experimental groups, the experimental group first
used upstream activities in the teaching material of literature and texts, the
second experimental group used the activities of building in the teaching
material itself and the experimental group the third use activities concluding
taught the same
(1)
This paper analyses the relationship between selected macroeconomic variables and gross domestic product (GDP) in Saudi Arabia for the period 1993-2019. Specifically, it measures the effects of interest rate, oil price, inflation rate, budget deficit and money supply on the GDP of Saudi Arabia. The method employs in this paper is based on a descriptive analysis approach and ARDL model through the Bounds testing approach to cointegration. The results of the research reveal that the budget deficit, oil price and money supply have positive significant effects on GDP, while other variables have no effects on GDP and turned out to be insignificant. The findings suggest that both fiscal and monetary policies should be fo
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
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